AI agent development
AI agent development company: what to ask before you hire one
A plain guide for business and IT leads comparing companies that build AI agents. The definitions and design advice come from Anthropic's own engineering article as read on 10 November 2026; the buying questions are Kriv AI's own view.
An AI agent development company designs, builds and tests software in which a language model uses tools to do work for you. Anthropic separates two kinds of system: workflows, where models and tools follow predefined code paths, and agents, where the model directs its own process and tool use. Anthropic advises finding the simplest solution possible and adding complexity only when needed, which may mean not building an agent at all. Our view: ask a company which kind it would build for your task, and why. Source read 10 November 2026.
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AI agent development company: what does one do?
An AI agent development company designs and builds systems where a language model can use tools, such as search, files or business applications, to complete a task. The work usually covers choosing the approach, connecting the tools, testing the result and handing it over to the people who run it.
Anthropic's engineering article describes two kinds of agentic system. Workflows are systems where language models and tools are orchestrated through predefined code paths. Agents are systems where the model dynamically directs its own process and tool use and keeps control over how it completes the task.
Source: Anthropic, Building effective AI agents (https://www.anthropic.com/research/building-effective-agents), published 19 December 2024, read 10 November 2026. The page carries a note that much of the tooling it describes has changed since publication.
comparison
Do you need an agent, or is a workflow enough?
Anthropic recommends finding the simplest solution possible and only increasing complexity when needed, which may mean not building an agentic system at all. It says agentic systems often trade latency and cost for better task performance. It says workflows offer predictability and consistency for well-defined tasks, while agents are the better option when flexibility and model-driven decision-making are needed at scale. For many applications, it adds, a single model call with retrieval and examples is enough.
Our reading for a buyer: a company that proposes a full agent for every task is not following this advice. A good proposal explains why your task needs the model to decide its own steps, or why a fixed workflow will do.
Source: Anthropic, Building effective AI agents (https://www.anthropic.com/research/building-effective-agents), read 10 November 2026.
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What should you ask an AI agent development company?
We suggest six questions. Which kind of system would you build for this task, a workflow or an agent, and why? What can the agent read, and what can it change? Which actions need a named person to approve them? How is every action logged so we can review it? How will you test it with our staff before it runs on real work? Who owns and maintains it after hand-over?
Anthropic also advises starting by using language model APIs directly, because frameworks can add layers of abstraction that hide the underlying prompts and responses and make problems harder to debug. If a company uses a framework, ask them to explain what it does underneath.
Source: Anthropic, Building effective AI agents (https://www.anthropic.com/research/building-effective-agents), read 10 November 2026.
kriv role
Where Kriv helps
Kriv AI designs and builds governed AI agents and workflows and trains the teams who work with them. Before a build we agree which tasks suit an agent, what it may reach, which actions a person approves and how each action is logged, then we build and test it with your staff.
Kriv did not write the article cited on this page. Scope and price are agreed after a short discovery call, and your own team keeps ownership of the process the agent supports.
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What this page could not confirm
This page rests on one Anthropic article, dated December 2024 and read on 10 November 2026, which itself says parts of its tooling discussion are out of date. We did not compare agent development companies, test any framework, or review any company's track record. Use the questions above as a starting point and check the current Anthropic documentation before you plan.
Straight answers
Frequently asked questions about AI agent development company: what to ask before you hire one
What does an AI agent development company do?
It designs, builds and tests systems where a language model uses tools to complete tasks, then hands them over to the people who run them. Anthropic separates workflows, which follow predefined code paths, from agents, where the model directs its own process (read 10 November 2026).
Do I need an AI agent or a simpler workflow?
Anthropic recommends the simplest solution possible and says that may mean not building an agentic system at all (read 10 November 2026). A fixed workflow suits well-defined tasks; an agent suits tasks that need flexibility.
What questions should I ask an AI agent development company?
Ask which kind of system they would build and why, what the agent can read and change, which actions a person approves, how actions are logged, how it is tested with your staff, and who owns it afterwards.
Are AI agent development services the same as AI consulting?
They overlap. Development builds the agent or workflow; consulting can also cover readiness, governance and training. Kriv AI does design, build, governance and training work.
How much do AI agent development services cost?
This page does not quote prices. Kriv AI scopes and prices work after a short discovery call, and our page on AI agent cost drivers explains what moves the cost.
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